Download Monohybrid Simple Dominance Model of Inheritance

Monohybrid Simple Dominance Model of
Inheritance
Consider the example of a trait for which two phenotypes are known. A cross between two individuals
with identical phenotypes that yields an F1 exhibiting the same phenotype as the parents can result
from any one of the following three crosses:
Cross 1
Phenotype 1
Cross 2
X
Phenotype 1
Phenotype 1
(AA)
(AA)
(AA)
Phenotype 1
X
Phenotype 1
(Aa)
Phenotype 1
Cross 3
Phenotype 2
X
Phenotype 2
(aa)
(aa)
Phenotype 2
The results of these crosses can be readily predicted through use of a Punnett Square:
Cross 1
AA X AA
Cross 2
Cross 3
AA X Aa
aa X aa
A cross between two individuals exhibiting different phenotypes that yields an F1 exhibiting two
different phenotypes results from the following cross:
Cross 4
Phenotype 1
(Aa)
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X
Phenotype 2
(aa)
Phenotypes 1
and 2
The results of this cross (a 1:1 ratio of Phenotype 1 to Phenotype 2) can readily be predicted through
use of a Punnett Square:
Cross 4
Aa X aa
A cross between two individuals with the same phenotype that yields an F1 exhibiting two different
phenotypes results from the following cross:
Cross 5
Phenotype 1
X
(Aa)
Phenotype 1
(Aa)
Phenotypes 1
and 2
The results of this cross (a 3:1 ratio of Phenotype 1 to Phenotype 2) can readily be predicted through
use of a Punnett Square:
Cross 5
Aa X Aa
A cross between two individuals with different phenotypes that yields an F1 with all the same
phenotype results from the following cross:
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Cross 6
Phenotype 1
X
(AA)
Phenotype 2
(aa)
Phenotype 1
The results of this cross (all Phenotype 1) can readily be predicted through use of a Punnett Square:
Cross 6
AA X aa
The above examples form the basis for understanding the inheritance of traits that exhibit a simple
dominance/recessive relationship. Of course, offspring ratios rarely exhibit the exact proportions that
are predicted from the above analysis. Therefore, the results must be tested statistically through use of
a goodness of fit test. Commonly, geneticists employ the Chi squared test to determine if the observed
results fit the predictions of one of the above models.
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